Gene detection system for promoting andrographolide synthesis based on biosensor

Abstract

The invention relates to the technical field of gene engineering detection, and particularly discloses a gene detection system for promoting andrographolide synthesis based on a biosensor, a key gene ApDof29 for regulating and controlling andrographolide synthesis is determined through whole genome analysis, gene expression profile research and co-expression network analysis, the core regulation and control effect of ApDof29 is verified, and the gene detection system for promoting andrographolide synthesis based on the biosensor is used for promoting andrographolide synthesis. The invention also develops a real-time dynamic monitoring system, and realizes non-invasive monitoring of andrographolide content accumulation, biosynthesis rate and metabolic intermediate concentration change by utilizing the fusion of a specific response element and a reporter gene. Through comprehensive calculation processing of an accumulation abnormal coefficient, a synthesis rate abnormal coefficient and a concentration change abnormal coefficient, the regulation and control effect of ApDof29 is dynamically evaluated, and a scientific basis is provided for subsequent gene modification.

Description

Technical Field

[0001] This invention relates to the field of gene engineering detection technology, and more specifically to a gene detection system based on biosensors for promoting andrographolide synthesis. Background Technology

[0002] Andrographis paniculata is a traditional Chinese medicinal herb with heat-clearing and detoxifying effects. Its main active ingredient, andrographolide, is a complex diterpenoid secondary metabolite with various pharmacological activities, including antibacterial, antiviral, anti-inflammatory, antitumor, and immunomodulatory effects. It has significant application value in modern medicine, especially in the traditional Chinese medicine industry. Currently, andrographolide is mainly extracted from plants. Although there are reports on chemical synthesis, its complex molecular structure, long synthetic pathway, and high cost pose significant challenges to economic efficiency and large-scale production. Furthermore, the generally low content of andrographolide in wild or cultivated Andrographis paniculata plants, along with poor extraction efficiency, results in high production costs, severely restricting its large-scale production and industrial application.

[0003] With the rapid development of molecular biology techniques, genetic engineering has provided new solutions for increasing the content of plant secondary metabolites and reducing production costs. However, the understanding of the regulatory mechanism of andrographolide biosynthesis remains incomplete, especially the key genes involved in biosynthesis and their regulatory networks, which have not been fully elucidated. This severely restricts the application prospects of precise regulation and targeted modification of andrographolide synthesis. Therefore, in-depth research on the key genes and regulatory mechanisms of the andrographolide biosynthesis pathway, especially the functional analysis of regulatory elements such as transcription factors, will not only help elucidate the molecular mechanism of andrographolide accumulation, but also provide theoretical basis and technical support for targeted enhancement of andrographolide yield through molecular breeding and genetic engineering, thereby promoting the sustainable development of andrographolide-related industries. This invention, through molecular biology methods such as gene cloning, discovered that ApDof29 can increase the synthesis and accumulation of andrographolide by regulating the expression of the key enzyme gene ApCPS2 in the andrographolide biosynthesis pathway. This demonstrates the core role of this gene in the andrographolide biosynthesis regulatory network, providing key functional gene markers and genetic manipulation targets for molecular breeding of andrographis paniculata.

[0004] The existing technology has the following shortcomings: Addressing the industry bottleneck of imperfect transcriptional regulation mechanisms for andrographolide biosynthesis and a lack of transcriptional regulatory genes leading to a lack of targets for metabolic engineering modification; This invention provides a novel ApDof29 transcription factor gene that significantly promotes the accumulation of andrographolide, providing a core gene resource for the targeted breeding of new varieties with high andrographolide content. Summary of the Invention

[0005] The purpose of this invention is to provide a gene detection system based on biosensors to promote the synthesis of andrographolide, in order to solve the problems mentioned above.

[0006] The objective of this invention can be achieved through the following technical solutions: A gene detection system based on biosensors to promote andrographolide synthesis includes: The target gene screening module screens and identifies the key gene ApDof29, which regulates andrographolide synthesis, through whole-genome analysis, gene expression profiling, and co-expression network analysis. The gene function verification module constructs a silenced strain of the ApDof29 gene using VIGS technology, and verifies whether ApDof29 plays a core role in andrographolide synthesis by combining the expression detection of the key enzyme gene ApCPS2 and the determination of andrographolide content. The real-time monitoring module, based on the core function verification results, constructs a dynamic monitoring system based on biosensors to monitor the accumulation of andrographolide content, biosynthesis rate and changes in the concentration of metabolic intermediates in real time, and dynamically evaluates the regulatory effect of ApDof29 on andrographolide synthesis based on the monitoring results and data analysis. The gene function modification and optimization module optimizes the function of the ApDof29 gene and increases the content of andrographolide through directed evolution.

[0007] As a further aspect of the present invention: the screening and identification of the key gene ApDof29, which regulates andrographolide synthesis, specifically includes: The entire genome of *Andrographis paniculata* was annotated, and specific gene families involved in the synthesis of secondary metabolites, including cytochrome P450 enzymes and transcription factors, were manually screened. Sequences highly similar to known andrographolide synthesis-related genes were identified as candidate genes through homology search. Differentially expressed genes were screened, and a gene co-expression network was established based on the list of differentially expressed genes. The betweenness centrality and proximity centrality values ​​of the nodes were calculated, and all genes were sorted according to the calculated betweenness centrality and proximity centrality values. Genes with betweenness centrality and proximity centrality values ​​higher than the network average were selected as candidates for key regulatory genes. If the initially screened candidates promoted andrographolide accumulation, the selected candidate ApDof29 was finally identified as the key gene regulating andrographolide synthesis.

[0008] As a further aspect of the present invention: the calculation process for the betweenness centrality value and the proximity centrality value is as follows: The calculation process for the betweenness centrality value is as follows: For each node in the constructed gene co-expression network, its betweenness centrality value is calculated using graph theory algorithms. Specifically, for each pair of nodes... and Count all shortest paths between nodes, if node If a node appears on these paths, its betweenness centrality value is incremented, based on the nodes traversed. The sum of the ratios of the number of shortest paths to the number of all shortest paths yields the betweenness centrality value. The calculation process for the approximation centrality value is as follows: Based on the gene co-expression network, a graph theory algorithm is used to calculate the proximity centrality value of each node. Specifically, the proximity centrality value is obtained by calculating the reciprocal of the average shortest path length from the node to all other nodes in the network.

[0009] As a further aspect of the present invention: the verification of whether ApDof29 plays a core role in the synthesis of andrographolide specifically includes: First, the ApDof29 gene was silenced in Andrographis paniculata using VIGS technology. With empty vector-infected plants as controls, the expression level of ApCPS2, a key enzyme gene involved in the biosynthesis of andrographolide, was detected by qRT-PCR. Andrographolide content was quantitatively determined by high performance liquid chromatography. If ApCPS2 expression was downregulated and andrographolide content decreased in the silenced plants, it was confirmed that ApDof29 plays a core regulatory role in andrographolide synthesis.

[0010] As a further aspect of the present invention: the dynamic evaluation of the regulatory effect of ApDof29 on andrographolide synthesis specifically includes: The system uses a biosensor dynamic monitoring system to collect real-time data on the accumulation of andrographolide content, biosynthesis rate, and concentration of metabolic intermediates. The collected real-time data is analyzed, and based on the analysis results, accumulation anomaly coefficients, synthesis rate anomaly coefficients, and concentration change anomaly coefficients are calculated. These coefficients are then comprehensively calculated using a comprehensive calculation expression to obtain the synthesis regulation coefficient. It is then determined whether the synthesis regulation coefficient is greater than or equal to a preset threshold. If it is, the regulation effect of ApDof29 on andrographolide synthesis is unqualified; otherwise, the regulation effect is qualified.

[0011] As a further aspect of the present invention: the process of obtaining the accumulated anomaly coefficient is as follows: Accumulated data on andrographolide content were collected in real time and organized into a matrix. The accumulated data on andrographolide content were then standardized to obtain a standardized matrix. The covariance matrix was calculated based on the accumulated data of the standardized andrographolide content. Perform eigenvalue decomposition on the covariance matrix to obtain eigenvalues. and the corresponding feature vector Eigenvalues ​​are sorted from largest to smallest; the top eigenvalues ​​are selected based on their cumulative contribution rate. The important eigenvalues ​​and their corresponding eigenvectors are used as principal components; the accumulated data of andrographolide content are projected onto the selected principal components to obtain a new coordinate matrix; the sum of the distances between the accumulated data of all andrographolide content and the data center in the principal component space is calculated to obtain the accumulation anomaly system.

[0012] As a further aspect of the present invention: the process for obtaining the synthesis rate anomaly coefficient is as follows: Time series data of biosynthesis rate is acquired and preprocessed to ensure data continuity and absence of missing values. Fluctuation sequences between adjacent time points are calculated. A series of scale parameters are determined, and for each scale parameter, the fluctuation sequence is segmented into segments of corresponding length, and the number of non-empty boxes is counted. Based on the relationship between the number of non-empty boxes at different scales and the scale parameters, the fractal dimension is estimated using a linear regression model. The anomaly coefficient of the biosynthesis rate is obtained based on the absolute value of the difference between the estimated fractal dimension and the expected fractal dimension under normal conditions.

[0013] As a further aspect of the present invention: the process for obtaining the concentration change anomaly coefficient is as follows: The process involves: acquiring time-series data on the concentrations of metabolic intermediates; preprocessing the time-series data to ensure continuity and absence of missing values; decomposing the preprocessed data using Haar wavelet transform to obtain a series of approximation coefficients and detail coefficients; calculating the energy of the detail coefficients at each Haar wavelet transform level and calculating the energy ratio of each level based on the sum of the energies of all Haar wavelet transform levels; comparing the calculated energy ratios with preset thresholds to determine which Haar wavelet transform levels' fluctuations are considered anomalous; and obtaining the concentration change anomaly coefficient based on the sum of proportions exceeding the set thresholds.

[0014] As a further aspect of the present invention: the directed evolution method optimizes the function of the ApDof29 gene, specifically including: A diverse gene pool was created using saturation mutagenesis, with the aim of introducing a large number of random mutations to cover a broad sequence space. High-throughput screening was used to evaluate the regulatory effect of each variant on andrographolide synthesis, and mutants with superior performance to wild-type were selected. The initially selected high-quality mutants were iteratively optimized in multiple rounds, and the mutation and screening process was repeated until the target variant that meets the expected functional improvement was obtained.

[0015] As a further aspect of the present invention: the method of increasing the content of andrographolide specifically includes: This study employed metabolic engineering strategies to regulate key steps in the andrographolide biosynthesis pathway. Specifically, it involved enhancing the precursor supply of isopentenyl pyrophosphate and dimethylpropenyl pyrophosphate in the acetate-mevaleric acid pathway, overexpressing diterpenoid cyclase genes responsible for diterpenoid skeleton formation to improve the efficiency of diterpenoid skeleton generation, optimizing the expression of key enzyme genes involved in oxidative modification and subsequent structural modification steps, including P450 monooxygenase and methyltransferase, and enhancing the positive regulatory effect of the ApDof29 gene on andrographolide synthesis-related genes by overexpression. The regulatory strategies were iteratively optimized to ultimately increase the andrographolide content.

[0016] An ApDof29 transcription factor gene from Andrographis paniculata, the CDS sequence of which is shown in SEQ ID NO:1.

[0017] A method for regulating andrographolide synthesis is achieved by regulating the expression level of the ApDof29 gene, wherein the regulation includes silencing the ApDof29 gene.

[0018] The beneficial effects of this invention are: (1) This invention precisely screened and identified the key gene ApDof29, which regulates andrographolide synthesis, and optimized its function using directed evolution. This not only significantly enhanced the positive regulatory effect of ApDof29 on andrographolide synthesis-related genes, but also achieved comprehensive optimization of the andrographolide biosynthesis pathway through a series of fine-tuning strategies. Specifically, we used metabolic engineering to overexpress the enzyme responsible for diterpene skeleton formation and optimized the expression of key enzyme genes, including P450 monooxygenase and methyltransferase. These measures jointly promoted the supply of andrographolide precursors, improved the conversion efficiency of intermediate products, and increased the accumulation of final products. In addition, based on the constructed biosensor dynamic monitoring system, real-time monitoring and feedback adjustment of the andrographolide synthesis process were achieved, ensuring the efficient operation of each step. This comprehensive strategy not only significantly increased the yield of andrographolide, but also provided solid technical support for the development of new varieties rich in andrographolide, demonstrating its great potential and broad application prospects in the improvement of medicinal plants and the efficient production of natural products.

[0019] (2) This invention innovatively constructs a dynamic monitoring system based on biosensors, realizing real-time and precise monitoring of andrographolide accumulation, biosynthesis rate, and metabolic intermediate concentration changes. This system cleverly integrates specific response elements with reporter genes (such as fluorescent proteins), enabling sensitive and continuous tracking of ApDof29 gene expression and its specific impact on the andrographolide biosynthesis pathway under in vivo conditions, providing a non-invasive research method. By calculating and analyzing accumulation anomaly coefficients, synthesis rate anomaly coefficients, and concentration change anomaly coefficients, we can dynamically evaluate the regulatory effect of ApDof29 in andrographolide synthesis and guide subsequent gene modification and optimization work. This integrated real-time monitoring and precise regulation platform not only significantly improves experimental efficiency and data accuracy but also provides strong technical support for in-depth analysis of the molecular mechanisms of andrographolide biosynthesis. Furthermore, the application of this system promotes the transformation from basic research to actual production, demonstrating its enormous potential and broad application prospects in increasing the yield of active ingredients in medicinal plants, which is of great significance for promoting the development of natural product synthetic biology. Attached Figure Description

[0020] The invention will now be further described with reference to the accompanying drawings.

[0021] Figure 1 This is a flowchart of the gene detection system for promoting andrographolide synthesis based on biosensors according to the present invention. Figure 2 This is a brain diagram of the gene detection system for promoting andrographolide synthesis based on biosensors, which is a schematic diagram of the present invention. Figure 3 This is a comparison chart of the andrographolide content of the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Example 1, please refer to Figure 1 As shown, this invention is a gene detection system for promoting andrographolide synthesis based on biosensors, comprising: The target gene screening module screens and identifies the key gene ApDof29, which regulates andrographolide synthesis, through whole-genome analysis, gene expression profiling, and co-expression network analysis. The gene function verification module constructs an ApDof29 gene-silenced strain using VIGS technology, and verifies whether ApDof29 plays a core role in andrographolide synthesis by combining the expression detection of the key enzyme gene ApCPS2 and the determination of andrographolide content. The real-time monitoring module, based on the core function verification results, constructs a dynamic monitoring system based on biosensors to monitor the accumulation of andrographolide content, biosynthesis rate and changes in the concentration of metabolic intermediates in real time, and dynamically evaluates the regulatory effect of ApDof29 on andrographolide synthesis based on the monitoring results and data analysis. The gene function modification and optimization module optimizes the function of the ApDof29 gene and increases the content of andrographolide through directed evolution.

[0024] Example 2, please refer to Figure 2 As shown, in the target gene screening module, through whole-genome analysis, gene expression profiling, and co-expression network analysis, the key gene ApDof29 regulating andrographolide synthesis was screened and identified, specifically including: Detailed genome annotation of Andrographis paniculata was performed, and specific gene families involved in secondary metabolite synthesis, including cytochrome P450 enzymes and transcription factors, were manually screened. Sequences highly similar to known andrographolide synthesis-related genes were identified as candidate genes through a rigorous homology search (using BLAST with an E value less than 1e-10). An experiment was designed to collect samples from Andrographis paniculata at different growth stages for RNA-seq sequencing. Differentially expressed genes were screened using DESeq2 with strict statistical thresholds, and their temporal dynamics were analyzed to verify the relevance of candidate genes. Based on the differentially expressed genes obtained through screening... A gene expression list was compiled, and a weighted gene co-expression network was constructed using a weighted gene co-expression network analysis method. After optimizing the soft threshold parameters, highly connected modules were identified, and functional enrichment analysis was performed on the genes within each module. The betweenness centrality and proximity centrality values ​​of the nodes were calculated, and all genes were ranked according to the calculated betweenness centrality and proximity centrality values. Genes with betweenness centrality and proximity centrality values ​​higher than the network average were selected as candidates for key regulatory genes. If the initially screened candidates could promote andrographolide accumulation, ApDof29 was ultimately identified as the key gene regulating andrographolide synthesis.

[0025] The network average is the mean of all betweenness centrality values ​​and the mean of all values ​​close to centrality.

[0026] The calculation process for the betweenness centrality value is as follows: For each node (i.e., gene) in the constructed gene co-expression network, its betweenness centrality value is calculated using graph theory algorithms. This value represents the frequency of a node's occurrence in all shortest paths. Specifically, for each pair of nodes... and Count all shortest paths between them, if the node If a path appears on these paths, its betweenness centrality value is increased. The expression for calculating the betweenness centrality value is: In the formula, Represents a node betweenness centrality value, Indicates from node To the node The number of all shortest paths, Indicates from node To the node All shortest paths passing through nodes Quantity, , and Represents nodes in a gene co-expression network; The calculation process for the proximity centrality value is as follows: Based on the gene co-expression network, a graph theory algorithm is used to calculate the proximity centrality value of each node. This value reflects the reciprocal of the average shortest path length from the node to all other nodes in the network, measuring the reachability of the node in the network. The expression for calculating the proximity centrality value is: In the formula, Represents a node and nodes The shortest path distance between them Represents a node The value close to centrality, It represents the set of all nodes in the network.

[0027] It's important to note that betweenness centrality measures a gene's importance as a "bridge" within a network; genes with high betweenness centrality are key points in signal transduction pathways. Proximity centrality reflects a gene's accessibility within the network; genes with high proximity centrality can rapidly exchange information with other genes or influence them. This series of steps provides a comprehensive research strategy, from the whole-genome level to specific functional validation, and ensures the uniqueness and accuracy of the results through meticulous data analysis and the application of bioinformatics tools.

[0028] In the gene function verification module, a silenced strain of the ApDof29 gene was constructed using VIGS technology. Combined with the expression detection of the key enzyme gene ApCPS2 and the determination of andrographolide content, the study verified whether ApDof29 plays a core role in andrographolide synthesis. Specifically, this included: First, the ApDof29 gene was silenced in Andrographis paniculata using VIGS technology. Then, using empty vector-infected plants as controls, the expression level of the key enzyme gene ApCPS2 (involved in the andrographolide biosynthesis pathway) was detected by qRT-PCR (quantitative reverse transcription polymerase chain reaction), and the andrographolide content was quantitatively determined by high-performance liquid chromatography. If ApCPS2 expression was downregulated and andrographolide content decreased in silenced plants, it could be confirmed that ApDof29 plays a core regulatory role in andrographolide synthesis.

[0029] It should be noted that by silencing the ApDof29 gene in Andrographis paniculata, combined with qRT-PCR detection of changes in the expression level of the key enzyme gene ApCPS2, and high-performance liquid chromatography (HPLC) determination of andrographolide content, the core regulatory role of ApDof29 in andrographolide synthesis was systematically verified. Experimental results showed that ApCPS2 expression was downregulated and andrographolide content was significantly reduced in ApDof29 VIGS plants. This not only reveals the crucial role of ApDof29 in regulating andrographolide biosynthesis but also provides a solid theoretical foundation and technical support for developing new varieties with high andrographolide yields based on this mechanism. This discovery enhances the understanding of the regulatory network of specific metabolic pathways and demonstrates important technological innovation and application prospects.

[0030] In the real-time monitoring module, based on the core function verification results, a biosensor-based dynamic monitoring system is constructed to monitor the accumulation of andrographolide, biosynthetic rate, and changes in the concentration of metabolic intermediates in real time. Based on the monitoring results and data analysis, the regulatory effect of ApDof29 on andrographolide synthesis is dynamically evaluated, specifically including: Based on the confirmed core regulatory role of ApDof29 in andrographolide synthesis, a biosensor-based dynamic monitoring system was constructed. Using synthetic biology methods, a biosensor capable of reflecting the real-time and sensitive expression level of the ApDof29 gene and its impact on andrographolide biosynthesis was designed and built. Specifically, by fusing a specific response element with a reporter gene (such as a fluorescent protein) and introducing it into target plant cells, the biosensor can specifically sense ApDof29, thereby activating reporter gene expression and generating quantifiable fluorescent signals or other easily detectable phenotypic changes. In this way, researchers can dynamically track the expression of ApDof29 and the related activities of the andrographolide biosynthesis pathway under in vivo conditions using simple optical measurement methods, such as fluorescence microscopy, achieving non-invasive and continuous monitoring of the target metabolic process.

[0031] It should be noted that a specific response element refers to a molecular component that can respond to a specific stimulus or condition within a cell and convert that response into a detectable signal. In constructing a biosensor-based dynamic monitoring system, a specific response element refers to a DNA sequence and protein that can specifically recognize and bind to a target molecule (such as the ApDof29 gene product).

[0032] The system uses a biosensor dynamic monitoring system to collect real-time data on the accumulation of andrographolide content, biosynthesis rate, and concentration of metabolic intermediates. The collected real-time data is analyzed, and based on the analysis results, accumulation anomaly coefficients, synthesis rate anomaly coefficients, and concentration change anomaly coefficients are calculated. These coefficients are then comprehensively calculated using a comprehensive calculation expression to obtain the synthesis regulation coefficient. It is then determined whether the synthesis regulation coefficient is greater than or equal to a preset threshold. If it is, the regulation effect of ApDof29 on andrographolide synthesis is unqualified; otherwise, the regulation effect is qualified.

[0033] The process of obtaining the accumulated anomaly coefficient is as follows: The accumulated data of andrographolide content were collected in real time and organized into a matrix, where each row of the matrix represents a sample and each column represents the andrographolide content at different time points or under different conditions. The accumulated data of andrographolide content collected in real time were standardized so that each feature has zero mean and unit variance. The covariance matrix was calculated based on the accumulated data of the standardized andrographolide content. The calculation expression is as follows: ; In the formula, Represents the covariance matrix. This indicates the number of accumulated data points on andrographolide content collected. This represents the accumulated data of standardized andrographolide content. This represents the transpose operation of a matrix; it also represents the eigenvalues ​​obtained by performing eigenvalue decomposition on the covariance matrix. and the corresponding feature vector These eigenvalues ​​represent the variance of the data in the corresponding directions, while the eigenvectors define these directions. The eigenvalues ​​are sorted from largest to smallest to determine which principal components are most important; the eigenvalues ​​are selected based on their cumulative contribution rate. Key eigenvalues ​​and their corresponding eigenvectors are selected as principal components, with eigenvalues ​​contributing 80%–95% cumulatively. The original data is projected onto the selected principal components to obtain a new coordinate matrix. Specifically, the data is mapped from the original high-dimensional space to a new space composed of principal components, simplifying the data structure while retaining as much information as possible. For each accumulated data point of andrographolide content, the sum of the distances between all accumulated andrographolide content data points and the data center in the principal component space is calculated to obtain the accumulation anomaly coefficient, expressed as follows: In the formula, Indicates the first The accumulation anomaly coefficient of the accumulation data of andrographolide content. This indicates the number of feature values ​​selected. Indicates the selected first 1 eigenvalue, Represents a coordinate matrix. This represents the mean of all coordinate matrices. Indicates the first Accumulated data on the content of andrographolide in individual samples.

[0034] The process for obtaining the anomaly coefficient of the synthesis rate is as follows: Time-series data of biosynthesis rate is acquired and preprocessed to ensure data continuity and absence of missing values. Fluctuation sequences between adjacent time points are calculated to capture changes in the biosynthesis rate. A series of scale parameters are determined, and for each scale parameter, the fluctuation sequence is segmented into segments of corresponding length, and the number of non-empty boxes is counted. Based on the relationship between the number of non-empty boxes at different scales and the scale parameters, the fractal dimension is estimated using a linear regression model. The biosynthesis rate anomaly coefficient is obtained based on the absolute value of the difference between the estimated fractal dimension and the expected fractal dimension under normal conditions. Specifically, for each selected scale parameter, the fluctuation sequence is segmented using box counting, and the number of non-empty boxes is counted; the calculation logic of the box counting method is as follows: In the formula, This represents a set of selected scale parameters. Indicates the number of non-empty boxes. Indicates the data collection points. This indicates the total number of data points collected. This indicates an indicator function that returns 1 if the condition is met, and 0 otherwise.

[0035] The fractal dimension is estimated using the following linear regression model: In the formula, For constant terms, at different scales and Perform linear regression; the slope is the fractal dimension.

[0036] The process for obtaining the concentration change anomaly coefficient is as follows: The process involves: acquiring time-series data on the concentrations of metabolic intermediates; preprocessing the time-series data to ensure continuity and absence of missing values; decomposing the preprocessed data using Haar wavelet transform to obtain a series of approximation coefficients and detail coefficients; calculating the energy of the detail coefficients at each Haar wavelet transform level and calculating the energy ratio of each level based on the sum of the energies of all Haar wavelet transform levels; comparing the calculated energy ratios with preset thresholds to determine which Haar wavelet transform levels' fluctuations are considered anomalous; and obtaining the concentration change anomaly coefficient based on the sum of proportions exceeding the set thresholds.

[0037] The decomposition of time series data into approximation coefficients at different levels using Haar wavelet transform is achieved recursively. For each Haar wavelet transform level, the energy of the detail coefficients is calculated, and the calculation expression is as follows: ; Indicates the first Each level of Haar wavelet transform This indicates the maximum transform level of the Haar wavelet transform. Indicates the first The first level of the Haar wavelet transform Detailed coefficients for the concentration of each metabolic intermediate. This indicates the number of metabolic intermediate concentration data at each Haar wavelet transform level. Indicates the first The energy of each Haar wavelet transform level is calculated by ratioing the energy of each Haar wavelet transform level to the sum of the energies of all Haar wavelet transform levels.

[0038] The comprehensive calculation expression is as follows: In the formula, , and As a preset scaling factor, and , and The sum of is 1. Represents the synthesis control coefficient. Indicates the accumulated outlier coefficient. Indicates the anomaly coefficient of the synthesis rate. This represents the coefficient of abnormal concentration change.

[0039] In the gene function modification and optimization module, the function of the ApDof29 gene was optimized using directed evolution methods, and the content of andrographolide was increased. Specifically, this included: Based on the evaluation results showing that ApDof29 has a satisfactory regulatory effect on andrographolide synthesis, the targeted evolution method for optimizing the function of the ApDof29 gene specifically includes: Directed evolution is a powerful technique that mimics the process of natural selection to optimize gene or protein function, particularly suitable for improving enzyme activity, stability, or other critical properties. Optimization of the regulatory effect of the ApDof29 gene on andrographolide synthesis can be achieved through traditional mutagenesis breeding, chemical mutagenesis, and adjustments to gene expression levels using classical genetic methods.

[0040] The process of optimizing the ApDof29 gene function using directed evolution first involves creating a diverse gene pool through saturation mutagenesis, aiming to introduce a large number of random mutations to cover a broad sequence space. High-throughput screening is then used to evaluate the regulatory effect of each variant on andrographolide synthesis, selecting mutants with superior performance compared to the wild type. These initially selected high-quality mutants undergo one or more rounds of iterative optimization, repeating the mutagenesis and screening process until the target variant meeting the expected functional improvement is obtained. Throughout this process, an efficient screening strategy ensures the rapid and accurate identification of ApDof29 variants with the desired characteristics.

[0041] The increase in andrographolide content specifically includes: This study employed a metabolic engineering strategy to regulate key steps in the andrographolide biosynthesis pathway. Specifically, this included enhancing the precursor supply of isopentenyl pyrophosphate and dimethylpropenyl pyrophosphate in the acetate-mevaleric acid pathway; overexpressing diterpenoid cyclase genes responsible for diterpenoid skeleton formation to improve the efficiency of diterpenoid skeleton generation; optimizing the expression of key enzyme genes involved in oxidative modification and subsequent structural modification steps, including P450 monooxygenase and methyltransferase; enhancing the positive regulatory effect of the ApDof29 gene on andrographolide synthesis-related genes by overexpressing the gene or optimizing its function using directed evolution; evaluating the improvement effects of each step using high-throughput screening technology; and iteratively optimizing the above regulatory strategies to ultimately achieve a significant increase in andrographolide content. The key steps include: the biosynthesis of andrographolide begins with isopentenyl pyrophosphate and dimethylpropenyl pyrophosphate produced via the acetate-mevaleric acid pathway. These are common precursors in the synthesis of all terpenoids. A series of condensation reactions form a more complex diterpenoid skeleton. This process is catalyzed by specific diterpenoid cyclases, which are the starting point for the specific biosynthesis of andrographolide. Optimizing this step can be achieved by overexpressing cyclases with high conversion capabilities. Starting from the initial diterpenoid skeleton, and through multiple modifications such as oxidation and methylation, andrographolide is finally formed. This involves the action of various enzymes, including P450 monooxygenases and methyltransferases. These enzymes precisely modify the molecule, increasing its chemical diversity and biological activity.

[0042] Key steps in modulating the andrographolide biosynthesis pathway using metabolic engineering strategies include controlling precursor supply, optimizing diterpene cyclase activity, and precisely regulating subsequent oxidative modification steps. Furthermore, by studying the specific function of ApDof29 in this process, its regulatory effect on target genes can be specifically enhanced or weakened, thereby effectively increasing the andrographolide content.

[0043] Example 3: An Andrographis paniculata transcription factor gene, ApDof29, the CDS sequence of which is shown in SEQ ID NO:1.

[0044] Functional domain annotation and homology analysis, specifically including: Confirmed by NCBI CDD and InterPro scans, the ApDof29 protein contains a typical Dof domain located between amino acid positions 34 and 89. Sequence alignment with Arabidopsis thaliana AtDof1.1 showed 84.2% homology, indicating that it belongs to the Dof transcription factor family.

[0045] The genome information of ApDof29 is shown in the table below: Cloning and sequence analysis of the ApDof29 gene:

[0046] The genome of ApDof29 was obtained directly from the cDNA of Andrographis paniculata plant via PCR amplification, as detailed below: Plant tissue origin: The purchased Andrographis paniculata seeds were sown in 12cm diameter round flowerpots filled with a 1:1 mixture of peat moss and vermiculite. These flowerpots were placed in a growth incubator set at 25℃ (temperature 25±2℃, photoperiod 16h light / 8h dark, relative humidity 60-70%). Tender leaves from healthy, two-week-old Andrographis paniculata seedlings were selected as experimental material, flash-frozen in liquid nitrogen, and then stored at -80℃ for later use.

[0047] RNA extraction methods: The preserved Andrographis paniculata leaf tissue was ground into powder in liquid nitrogen. Approximately 100 mg was taken and total RNA was extracted using the RNeasyPlant Mini RNA Isolation Kit (QIAGEN, Germany). Subsequently, it was reverse-engineered into cDNA using the HiScript III 1st Strand cDNA Synthesis Kit (+gDNA wiper) (Vazyme).

[0048] Primers were designed based on the ApDof29 gene sequence annotated in the Andrographis paniculata genome data, with BamHI and KpnI restriction sites introduced at the 5' ends of the forward and reverse primers, respectively. The specific sequences are as follows: Forward primer (Tri1-F-BamHI): 5'-CGGGATCCATGCAAGGCATGCACGCCGT-3' (SEQ ID NO:4); Reverse primer (Tri1-R-KpnI): 5'-GGGGTACCTTACTGGGAAAGAAAATTAAGGG-3' (SEQ IDNO: 6).

[0049] The CDS of ApDof29 was amplified from leaf cDNA using the high-fidelity enzyme KOD. A 50 μL PCR reaction mixture contained: 5 μL 10× PCR buffer, 5 μL 2 mM dNTPs, 3 μL 25 mM MgSO4, 1.5 μL each of primers (forward and reverse), 1 μL DNA, and 33 μL ddH2O. The amplification program was: 94℃ pre-denaturation for 2 min; 98℃ denaturation for 10 s, 58℃ annealing for 30 s, and 68℃ extension for 1 min, for a total of 35 cycles; and a final extension at 68℃ for 10 min.

[0050] The ApDof29 CDS was cloned into the pGreen0062SK vector between the BamHI and KpnI sites using an enzyme digestion and ligation cloning method. The constructed recombinant plasmid was transformed into *E. coli* DH5α competent cells and screened on LB medium containing 50 μg / mL⁻¹ kanamycin. Clones that tested positive for antibiotics and PCR were sent to Shanghai Sangon Biotech for sequencing analysis.

[0051] Sequence characteristics: The CDS sequence of ApDof29 is shown in SEQ ID NO:1, the full-length genome sequence is shown in SEQ ID NO:2, and the promoter sequence (approximately 1.5 kb) is shown in SEQ ID NO:3.

[0052] The gene is located in the Andrographis paniculata genome scaffold NW_026137621.1 (gene ID: LOC127241596), with start and stop sites of 3873537-3874762, and is in the negative strand direction.

[0053] Example 4: Virus-Induced Gene Silencing (VIGS) Experiment Based on the ApDof29 CDS sequence, a suitable fragment was selected and cloned into the pLY156 (pTRV2) vector between the BamHI and XhoI sites. The primers used were: Forward primer (Tri1-F-BamHI): 5'-CGGGATCCATGCAAGGCATGCACGCCGT-3' (SEQ ID NO:4); Reverse primer (Tri1-R-XhoI): 5'-CCGCTCGAGTGAAGGAGCATCTGCGTCG-3' (SEQ ID NO: 5).

[0054] The constructed recombinant plasmids, along with the empty pTRV1 and pTRV2 vectors, were transformed into competent Agrobacterium GV3101 cells and screened on LB medium containing 50 μg·mL⁻¹ kanamycin and 50 μg·mL⁻¹ rifampin. The Agrobacterium culture was incubated overnight at 28°C and 200 rpm with shaking until the OD600 reached approximately 1.0. The cells were then collected by centrifugation and resuspended in infection buffer (10 mM MgCl2, 10 mM MES, pH 5.6, 100 mM acetylsylcholine) to adjust the OD600 to 1.0. pTRV1 and pTRV2 (empty vector or recombinant vector containing the ApDof29 insert) were mixed at a 1:1 volume ratio and incubated at room temperature for 2–4 h. Healthy Andrographis paniculata plants at the four-leaf stage were then treated using a vacuum infection method. After vacuum treatment, the plants were rinsed with clean water and cultured under normal greenhouse conditions for 10 days for subsequent determination of andrographolide content and qPCR analysis.

[0055] (1) qPCR analysis Total RNA was extracted using a polysaccharide-polyphenol plant total RNA extraction kit (Vazyme, China). cDNA was synthesized via reverse transcription using a HiScript III RT SuperMix for qPCR (+gDNA wiper) (Vazyme, China) according to the kit instructions. qPCR amplification was performed using the cDNA as a template, and gene expression was detected using the SYBR Green qPCR method. The primers are as follows: ApACT: Forward 5′-ACGATGTTCACGGGCATTG-3′, Reverse 5′-GAGCCACCACCTTGATCTTCA-3′ ApCPS2: Forward 5′-CAGAGTCGGTGTGCAGCAA-3′, Reverse 5′-CCAACTCCTCCATCTCCGATT-3′ ApDof29: Forward 5′-GGCGACGGAAGAGCTAAAGA-3′, Reverse 5′-GCTGACTCCAGTACGCAAGA-3′.

[0056] The 20 μL qPCR reaction system consisted of: 10 μL 2× ChamQ Universal SYBR qPCR MasterMix, 0.4 μL each of forward and reverse primers, 1 μL cDNA, and 8.2 μL ddH2O. The qPCR reaction program was as follows: pre-denaturation at 95℃ for 30 s; followed by 40 cycles (95℃ for 10 s, 60℃ for 30 s); and finally, melting curve analysis (95℃ for 15 s, 60℃ for 60 s, 95℃ for 15 s).

[0057] The results are as follows Figure 3 As shown, the expression levels of ApDof29 and ApCPS2 were significantly reduced in VIGS plants.

[0058] (2) Determination of andrographolide content The content of andrographolide was determined by HPLC. The results are as follows: Figure 3 As shown, the content of andrographolide in ApDof29 silent plants was significantly reduced compared with the control.

[0059] This invention successfully cloned and identified the Andrographis paniculata transcription factor gene ApDof29, and demonstrated through VIGS experiments that it positively regulates the biosynthesis of andrographolide. This gene can be used in Andrographis paniculata metabolic engineering to increase the yield of andrographolide.

[0060] The working principle of this invention's biosensor-based gene detection system for promoting andrographolide synthesis is as follows: It utilizes a series of advanced molecular biology and metabolic engineering techniques to increase the content of andrographolide. The target gene screening module identifies the key gene ApDof29, which regulates andrographolide synthesis, through whole-genome analysis, gene expression profiling, and co-expression network analysis. Through rigorous homology searching, RNA-seq sequencing, and weighted gene co-expression network analysis, ApDof29 is identified as a key regulatory factor. Next, the gene function verification module constructs ApDof29-silenced plants using VIGS technology and, combined with the expression detection of the key enzyme gene ApCPS2 and the determination of andrographolide content, verifies the core role of ApDof29 in andrographolide synthesis. Subsequently, based on the confirmed core regulatory role, the real-time monitoring module constructed a biosensor-based dynamic monitoring system. This system can monitor the accumulation of andrographolide, biosynthetic rate, and concentration changes of metabolic intermediates in real time. By calculating the accumulation anomaly coefficient, synthesis rate anomaly coefficient, and concentration change anomaly coefficient, the regulatory effect of ApDof29 on andrographolide synthesis is comprehensively evaluated. Finally, in the gene function modification and optimization module, a diverse ApDof29 gene library was created using directed evolution. After high-throughput screening and multiple rounds of iterative optimization, high-performance variants were selected, significantly increasing the content of andrographolide. In addition, the biosynthetic pathway of andrographolide was further enhanced by improving the supply of precursor substances, optimizing the activity of diterpenoid cyclase, and subsequent oxidative modification steps. The entire technical solution not only reveals the key role of ApDof29 in andrographolide synthesis but also provides a solid theoretical foundation and technical support for developing new varieties that efficiently produce andrographolide, demonstrating important technological innovation and application prospects.

[0061] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A gene detection system for promoting andrographolide synthesis based on biosensors, characterized in that, include: The target gene screening module screens and identifies the key gene ApDof29, which regulates andrographolide synthesis, through whole-genome analysis, gene expression profiling, and co-expression network analysis. The screening and identification of ApDof29, a key gene regulating andrographolide synthesis, specifically includes: The entire genome of *Andrographis paniculata* was annotated, and specific gene families involved in the synthesis of secondary metabolites, including cytochrome P450 enzymes and transcription factors, were manually screened. Sequences highly similar to known andrographolide synthesis-related genes were identified as candidate genes through homology search. Differentially expressed genes were screened, and a gene co-expression network was constructed based on the list of differentially expressed genes. The betweenness centrality and proximity centrality values ​​of the nodes were calculated, and all genes were sorted according to the calculated betweenness centrality and proximity centrality values. Genes with betweenness centrality and proximity centrality values ​​higher than the network average were selected as candidates for key regulatory genes. If the initially screened candidates promoted andrographolide accumulation, the screened candidate ApDof29 was finally identified as the key gene regulating andrographolide synthesis. The gene function verification module constructs a silenced strain of the ApDof29 gene using VIGS technology, and verifies whether ApDof29 plays a core role in andrographolide synthesis by combining the expression detection of the key enzyme gene ApCPS2 and the determination of andrographolide content. The real-time monitoring module, based on the core function verification results, constructs a dynamic monitoring system based on biosensors to monitor the accumulation of andrographolide content, biosynthesis rate and changes in the concentration of metabolic intermediates in real time, and dynamically evaluates the regulatory effect of ApDof29 on andrographolide synthesis based on the monitoring results and data analysis. The gene function modification and optimization module optimizes the function of the ApDof29 gene and increases the content of andrographolide through directed evolution. The increase in andrographolide content specifically includes: This study employed metabolic engineering strategies to regulate key steps in the andrographolide biosynthesis pathway. Specifically, it involved enhancing the precursor supply of isopentenyl pyrophosphate and dimethylpropenyl pyrophosphate in the acetate-mevaleric acid pathway, overexpressing diterpenoid cyclase genes responsible for diterpenoid skeleton formation to improve the efficiency of diterpenoid skeleton generation, optimizing the expression of key enzyme genes involved in oxidative modification and subsequent structural modification steps, including P450 monooxygenase and methyltransferase, and enhancing the positive regulatory effect of the ApDof29 gene on andrographolide synthesis-related genes by overexpressing the gene. The regulatory strategy was iteratively optimized to ultimately increase the andrographolide content. The key steps include: the biosynthesis of andrographolide begins with isopentenyl pyrophosphate and dimethylpropenyl pyrophosphate produced by the acetic acid-mevaleric acid pathway; these are common precursors for the synthesis of all terpenoid compounds; a series of condensation reactions form a more complex diterpenoid skeleton; catalysis by diterpenoid cyclase is the starting point for the specific biosynthesis of andrographolide; starting from the initial diterpenoid skeleton, and after multiple oxidation, methylation and other modifications, andrographolide is finally formed.

2. The gene detection system for promoting andrographolide synthesis based on a biosensor according to claim 1, characterized in that, The calculation process for the betweenness centrality value and the proximity centrality value is as follows: The calculation process for the betweenness centrality value is as follows: For each node in the constructed gene co-expression network, its betweenness centrality value is calculated using graph theory algorithms. Specifically, for each pair of nodes... and Count all shortest paths between nodes, if node If a node appears on these paths, its betweenness centrality value is incremented, based on the nodes traversed. The sum of the ratios of the number of shortest paths to the number of all shortest paths yields the betweenness centrality value. The calculation process for the approximation centrality value is as follows: Based on the gene co-expression network, a graph theory algorithm is used to calculate the proximity centrality value of each node. Specifically, the proximity centrality value is obtained by calculating the reciprocal of the average shortest path length from the node to all other nodes in the network.

3. The gene detection system for promoting andrographolide synthesis based on a biosensor according to claim 1, characterized in that, The verification of whether ApDof29 plays a key role in the synthesis of andrographolide specifically includes: First, the ApDof29 gene was silenced in Andrographis paniculata using VIGS technology. With empty vector-infected plants as controls, the expression level of ApCPS2, a key enzyme gene involved in the biosynthesis of andrographolide, was detected by qRT-PCR. Andrographolide content was quantitatively determined by high performance liquid chromatography. If ApCPS2 expression was downregulated and andrographolide content decreased in the silenced plants, it was confirmed that ApDof29 plays a core regulatory role in andrographolide synthesis.

4. The gene detection system for promoting andrographolide synthesis based on a biosensor according to claim 1, characterized in that, The dynamic evaluation of the regulatory effect of ApDof29 on andrographolide synthesis specifically includes: The system uses a biosensor dynamic monitoring system to collect real-time data on the accumulation of andrographolide content, biosynthesis rate, and concentration of metabolic intermediates. The collected real-time data is analyzed, and based on the analysis results, accumulation anomaly coefficients, synthesis rate anomaly coefficients, and concentration change anomaly coefficients are calculated. These coefficients are then comprehensively calculated using a comprehensive calculation expression to obtain the synthesis regulation coefficient. It is then determined whether the synthesis regulation coefficient is greater than or equal to a preset threshold. If it is, the regulation effect of ApDof29 on andrographolide synthesis is unqualified; otherwise, the regulation effect is qualified.

5. The gene detection system for promoting andrographolide synthesis based on a biosensor according to claim 4, characterized in that, The process of obtaining the accumulated anomaly coefficient is as follows: Accumulated data on andrographolide content were collected in real time and organized into a matrix. The accumulated data on andrographolide content were then standardized to obtain a standardized matrix. The covariance matrix was calculated based on the accumulated data of the standardized andrographolide content. Perform eigenvalue decomposition on the covariance matrix to obtain eigenvalues. and the corresponding feature vector ; Eigenvalues ​​are sorted from largest to smallest; the top eigenvalues ​​are selected based on their cumulative contribution rate. The important eigenvalues ​​and their corresponding eigenvectors are used as principal components; the accumulated data of andrographolide content are projected onto the selected principal components to obtain a new coordinate matrix; the sum of the distances between the accumulated data of all andrographolide content and the data center in the principal component space is calculated to obtain the accumulation anomaly coefficient.

6. The gene detection system for promoting andrographolide synthesis based on a biosensor according to claim 4, characterized in that, The process for obtaining the anomaly coefficient of the synthesis rate is as follows: Time series data of biosynthesis rate is acquired and preprocessed to ensure data continuity and absence of missing values. Fluctuation sequences between adjacent time points are calculated. A series of scale parameters are determined, and for each scale parameter, the fluctuation sequence is segmented into segments of corresponding length, and the number of non-empty boxes is counted. Based on the relationship between the number of non-empty boxes at different scales and the scale parameters, the fractal dimension is estimated using a linear regression model. The anomaly coefficient of the biosynthesis rate is obtained based on the absolute value of the difference between the estimated fractal dimension and the expected fractal dimension under normal conditions.

7. The gene detection system for promoting andrographolide synthesis based on biosensors according to claim 4, characterized in that, The process for obtaining the concentration change anomaly coefficient is as follows: The process involves: acquiring time-series data on the concentrations of metabolic intermediates; preprocessing the time-series data to ensure continuity and absence of missing values; decomposing the preprocessed data using Haar wavelet transform to obtain a series of approximation coefficients and detail coefficients; calculating the energy of the detail coefficients at each Haar wavelet transform level and calculating the energy ratio of each level based on the sum of the energies of all Haar wavelet transform levels; comparing the calculated energy ratios with preset thresholds to determine which Haar wavelet transform levels' fluctuations are considered anomalous; and obtaining the concentration change anomaly coefficient based on the sum of proportions exceeding the set thresholds.

8. The gene detection system for promoting andrographolide synthesis based on a biosensor according to claim 1, characterized in that, The directed evolution method optimizes the function of the ApDof29 gene, specifically including: A diverse gene pool was created using saturation mutagenesis, with the aim of introducing a large number of random mutations to cover a broad sequence space. High-throughput screening was used to evaluate the regulatory effect of each variant on andrographolide synthesis, and mutants with superior performance to wild-type were selected. The initially selected high-quality mutants were iteratively optimized in multiple rounds, and the mutation and screening process was repeated until the target variant that meets the expected functional improvement was obtained.

9. An Andrographis paniculata transcription factor gene, ApDof29, wherein the gene detection system for promoting andrographolide synthesis based on a biosensor as described in any one of claims 1-8 is characterized in that: The CDS sequence of the ApDof29 gene is shown in SEQ ID NO:

1.

10. A method for regulating andrographolide synthesis, comprising using the andrographolide transcription factor gene ApDof29 as described in claim 9, characterized in that, This is achieved by regulating the expression level of the ApDof29 gene, including silencing the ApDof29 gene.

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